AI Founders and Executives Predict 5-Year Trends on Consumer Tech

Daniel Faggella is the founder and CEO at Emerj. Called upon by the United Nations, World Bank, INTERPOL, and many global enterprises, Daniel is a sought-after expert on the competitive strategy implications of AI for business and government leaders.

It’s been over a month since our last major artificial intelligence consensus (which covered 33 AI researcher perspectives on the 20-year risks of AI), and we decided that this time around, we’d speak with AI executives directly about the future of artificial intelligence and machine learning in consumer tech.

The media is awash with buzz-stories about autonomous vehicles, speech recognition, robotics, and more, but it seems difficult to glean a perspective on which consumer AI tech trends are likely to make the biggest impact in the coming 5 years.

While there’s certainly no crystal ball, our preference as a market research firm is to combine research and news analysis with a strong consensus from dozens of experts in the field. When it comes to AI for consumer tech, we decided to ask executives and founders of artificial intelligence companies what they believe to be the most important AI consumer tech trends in the next half decade.

You can see a full list of the answers to our “AI Consumer Tech Trends” below in our large infographic.

Note: The data for this graphic is no longer available publicly and are only available for Emerj research members. This change was enacted in November 2018.

By far the most common trend predictive was “Virtual Agents / Chatbots”, even among AI executives in fields unrelated to virtual agents. I assume that the attention around the efforts of Amazon (Echo), Facebook (M) and other tech giants has this topic at the forefront of consumer tech attention.

Bear in mind that the “categorization” was done after the fact (it could be argued that other categories could have been used to couch these responses), and that 35 executives and founders is by no means an extensive consensus. However, the top trends (and insightful related quotes from execs around the world) are worth considering for anyone making bets on AI in consumer tech in the years ahead.

The year 2015 might be seen as the year that "artificial intelligence risk" or "artificial intelligence danger" went mainstream (or close to it). With the founding of Elon Musk's Open AI and The Leverhulme Centre for the Future of Intelligence; the increased attention on the Future of Life Institute and Oxford's Future of Humanity Institute; and a flurry of attention around celebrity comments around AI dangers (including the now well-known statements of Bill Gates and Elon Musk), it's safe to say that the risks of AI has embedded itself as a topic of pop-culture discourse — even if it's not a very serious one amongst the populace at present.

Artificial intelligence and machine learning adoption among different industries represents a new chapter in digital transformation. However, according our own research across industries, AI adoption in 2017 remains low with majority of major success stories coming only from the largest tech players in the industry (Google, Baidu, Apple, etc). McKinsey Global Institute estimates that in 2016, tech giants invested $20-30 billion into AI, while smaller companies altogether invested an estimated $6-9 billion.

The last few years have yielded a tremendous amount of attention at the intersection of AI and healthcare, from DeepMind's partnership with the UK's National Health Service to IBM's continued pushes into areas of genomics and drug discovery. From the perspective of healthcare executives, however, many important questions are left unanswered and rarely addressed in detail: What difference are healthcare's machine learning innovations likely to make in the lives of patients? What disruptions should healthcare executives prepare themselves for now? How will the healthcare industry operate differently in 5 or 10 years into the future? We surveyed over 50 executives of healthcare companies leveraging AI. We aimed to do the hard work of separating the companies actually applying AI from those who use it as a buzzword (over 15 of our initial survey responses were turned down due to lack of evidence of real AI in use), presenting important predictions and industry insights in clear and interactive charts and graphs. The following research article is broken down into five sections:

Back at the beginning of the year, I set out to get a feel for a city in the longitudinal center of the country, between two coastal tech hubs in San Francisco and NYC: Austin. I wanted to find out what made Austin an attractive AI and tech hub the way I had in Boston, Atlanta, Montreal, and Bangalore before it. It turns out the AI startup community in Austin is measurably different than those on the east and west coast, and it stood out to me in the way it was able to offer a quality of life that's rare for fresh-out-of-college talent on the coasts.

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